Mechanisms by which inflammation may increase intestinal cancer risk in inflammatory bowel disease
Bibliographic record
Abstract
Patients with ulcerative colitis and Crohn's disease are at increased risk of developing intestinal cancers via mechanisms that remain incompletely understood. However, chronic inflammation and repeated events of inflammatory relapse in inflammatory bowel disease (IBD) expose these patients to a number of signals known to have tumorigenic effects including persistent activation of the nuclear factor-kappaB and cyclooxygenase-2/prostaglandin pathways, release of proinflammatory mediators such as tumor necrosis factor-alpha and interleukin-6, and enhanced local levels of reactive oxygen and nitrogen species. These inflammatory signals can contribute to carcinogenesis via 3 major processes: 1) by increasing oxidative stress, which promotes DNA mutagenesis thus contributing to tumor initiation; 2) by activating prosurvival and antiapoptotic pathways in epithelial cells, thereby contributing to tumor promotion; and 3) by creating an environment that supports sustained growth, angiogenesis, migration, and invasion of tumor cells, thus supporting tumor progression and metastasis. The present review integrates clinical and basic research observations in an attempt to provide a comprehensive understanding of how inflammatory processes may contribute to intestinal cancer development in IBD patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".